The modern world is seemingly flooded with data but is often at a loss for interpreting it. One exceptionally useful tool that has found wide acceptance is software that presents the data in some visual form, especially in a way that makes relationships noticeable. Using this software, often very complex databases can be queried. The results of the queries are then analyzed and displayed in some visual format, usually graphical, such as a bar or pie chart, scatter plot, or any of a large number of other well-known formats. Modern analysis tools then allow the user to dynamically adjust the ranges of the displayed results in order to change and see different aspects of the analysis.
One prominent data visualization product is owned by Spotfire AB of Göteborg, Sweden, and marketed under the name DecisionSite.® In this product, which incorporates the technology disclosed in U.S. Pat. No. 6,014,661 (Ahlberg, et al., “System and method for automatic analysis of data bases and for user-controlled dynamic querying,” issued 11 Jan. 2000, and herein incorporated by reference), query devices tied to columns in the data set and different visualizations of the data allow users to dynamically filter their data sets based on any available property, and hence to interactively visualize the data. As the user adjusts graphical query devices such as rangesliders and alphasliders, the DecisionSite® product changes the visualization of the data accordingly.
The DecisionSite® product also includes several other automatic features, such as initial selection of suitable query devices and determination of ranges, which aid the user not only to visualize the data, but also to mine it. When properly used, this technique constitutes a powerful tool that forms the basis for sophisticated data exploration and decision-making applications.
Overall, analysis and visualization products have improved the efficiency and enhanced the capabilities of professionals in a wide range of areas of data analysis. But these individuals are typically highly trained and highly paid, and they can still spend long periods of time in their data analysis tasks. Improvements in the efficiency of data analysis tasks would therefore be of great benefit to individuals working in a variety of areas.